Statistics
When first met with Monte Hall problem and Simpson's paradox, I found
Statistics quite interesting. After a deeper analysis on such issues, I find it
logical and rational. (-Jeff: can you give a specific example to show
why it is interesting?) Nowadays, as we can see where there are data, there is
Statistics. Abstracting knowledge from massive data; applying statistical
methods to various disciplines; exploring rule and truth by statistical
techniques\ldots(-Jeff: exploring rule and truth in what?) They are all about
Statistics, which I have been engaged myself in for my entire undergraduate's
life and in which I decide to pursue a career.

Academic Experience
As the GPA of 3.96 in my major Math & Stat courses shows, I have little
difficulty in understanding the main ideas and methods in study. Meanwhile, I
like discussing questions and sharing what I know with others. So I served as
the role of TA in many courses. In Numerical Analysis, whose difficulties all
lie in calculating, I wrote scripts to realize nearly all algorithms provided
in our textbook, using C, R and MATLAB. It is wonderful experiences to see
laborious computations become easy and fast(-Jeff: what do you want to
emphasize by this sentence? Do you mean you like programming?). As my preference
of tackling problems in a computational way matches the idea of Prof. Yubin
Tian(one of my recommenders), who aims to employ computational methods in
experiment design, I was invited by her to give classmates lectures
on theory deduction and software operation in her course Design of Experiments
(DOE). I took on the task immediately and spent two weeks on reading papers,
gathering materials, making summaries and writing scripts. These efforts endded
in three class lectures to present the techniques in experiment design, ANOVA
and displaying them in a computational way, by operating with
various softwares such as MINITAB, SAS, STATE and SPSS, and one lecture on
statistical theory about Saturated and Supersaturated Design. During these
lectures, both my classmates and Prof. Tian proposed several difficult
questions. Nevertheless, due to my sufficient preparation, I was able
to answer them in detail in a short time. I felt proud that they were satisfied
with my answers; and I was also delighted to see that my classmates started
to learn and use statistical softwares at ease in their later studies.
During Oct. 2008 and Apr. 2009 I organized a mathematical modeling team with
two other students and participated in two modeling contests: China
Undergraduate Mathematical Contest in Modeling (CUMCM) and The Mathematical
Contest in Modeling (MCM/ICM). In CUMCM, which is the biggest
mathematical modeling contest available for all university
students in all disciplines in China, we won a national second prize; and in
MCM/ICM, a famous world-wide mathematical contest, our team was designated as
the Meritorious Winner. The experiences as the leader of our team in these two
modeling contests make me prepared when facing real world problems, which are
tough but fascinating. In CUMCM, how to deal with the massive data was the key
problem. Our team tackled the problem by employing a new AHP model, combined
with correlation analysis, regression and optimization. As you can see, this
time, Statistics played a vital role in our approach. In MCM/ICM, however, we
are facing a more much difficult Roundabout problem, and how to reformulate the
problem in a mathematical way is really challenging. At the very beginning, our
team even had hard a time on debating on how to understand the problem.
Fortunately, after innumerable hot discussions and in-depth analysis of the
problem, we finally came out a nice approach for it. Based on it, we
designed a new roundabout and contructed several mathematical models, and this
idea and innovation turned out to be a success in the end. Through the experiences of
little sleep, intenstive discussions and even hot debates in these modeling
contests, I gained much deeper understandings in cooperation, persistence and
innovation. 
Interest is the best teacher. To follow my interest in learning new
statistical techniques, I went to Tsinghua Univeristy every morning before 7
o'clock to attend the Summer School, which lectured by three Harvard
professors, Prof. Xihong Lin, Yi Li and Sam Kou. Beside the new knowledge on
semi-&non-parametric methods, Monte Carlo methods and survival analysis
obtained in class, I also learned that we should have a good attitude towards
(-Jeff: I don't understand the logic in this sentence. what do you mean by 'a
good attitude'?) research work, and a broad view by combining Statistics with
other branches of disciplines. As Prof. Sam Kou told us, a statistical method
cann't be called good unless it could help solve real-world problem. To follow
my interest and broad my view on Statistics, I explored into issues
related to areas such as data mining, machine learning and biostatistics.
Also, I went to Renmin University frequently to take classes on Applied
Statistics in Economics, and joined the Summer Camp held in Beijing Normal
University for Outstanding Undergraduates in Math & Statistics. This year, our
team applies a SRIT program. (See Attachment)(-Jeff: oh, why this sentence
here?)
From these experiences, I get one thing: follow your interest, be persistent
and innovative, you will finally gain happiness.

Career Goal & Research
Statistics applications in Biology become necessary and popular in recent
years because more and more concerns are given on human health, especially after
the establishment of Human Genome Project (HGP). I am highly motivated by the
prospective of analyzing massive data and uncovering the myth between gene and
illness. My career goal is to be researcher in applied statistics, especially
in the interdisciplinary area between Statistics and Biology, to develop new
techniques, to analyze more thoroughly (-Jeff: to do what?), and to make
compuatation more easily. 
Problem is the heart of research(-Jeff: what do you mean?). To get familiar
with Biostatistics, I need more experience and should have a comprehensive view
of the current problems in Biology. Thanks to my outstanding academic
performance, Prof. H.X Lei, researcher in Beijing Institution of Genomics
(BIG), invited me to join in his research group as an internship. Now I am
working with him on two research projects (See more in the attachment). Despite the only
undergraduate student in the group, I am confident that I could gain much
experience from and in the meantime contribute to the research work.

Why PhD & Why Harvard
During my study in BIG, I find that if I want to make huge steps in solving
problems related to data analysis, I need to learn more statistical
techniques. And to make breakthrough in this area (-Jeff: which area?),
developing new statistical tools in necessary. In order to reach my goal, I
should have more study and research on statistical methods and their
applications. [ While in China, where people make decisions mainly based
on their experiences and institutions put less emphasis on statistical analysis
and inference, academic environment is not so good for studying Statistics
systematically. ](-Jeff: Can you remove this sentence?) Pursuing further in
academics(-Jeff: academics?) in Biostatistics at Harward University will provide
me with greate opportunity to expose myself to the pioneering work directed by
Harward's professors. With its solid background in Bayesian Statistics and
computation, with particular concerns on public health, and intensive
collaborations with Department of Statistics, HMS(-Jeff: what's the full name
of HMS?) and other institutions world-wide, Harward's Biostatistics programs
will equip me with strong foundation in and comprehensive prespectives of
Biostatistics. I look forward to the time when I could work with Prof. Jun Liu
on interesting problems like predicting gene regulatory binding motifs, and with
Prof. Xihong Lin and Prof. Yi Li on longitudinal data analysis. My trainings,
experiences, as well as motivations get me ready for the harward's challenging
graduate study and will surely contribute to the field of Biostatistics.

SRIT program
The program will focus on improvement of methods in predicting the relationship
between SNPs (-Jeff: what is the full name of SNP?)(especially cSNPs) and human
illness, aiming at increasing the accuracy of predications based on Support
Vector Machine (SVM).

What I am doing in BIG
I am now working on two projects with two different teams. One team focuses on
Structure Biology to improve or compose new scoring function, which is an
important method (also an active research area) in protein structure prediction
and protein-protein docking. We are now trying to find out the key factors which
influence protein's structure, reformulate their relations, and select the right
coefficients for the formulation we set. By introducing Grid Search and Jack's
Knife Test into their original ideas(-Jeff: who is 'their'?), we are now making
progresses in composing the scoring function. The other team centers on System
Biology and our project deals with another tough problem: neurodegenerative
disease. Different from previous approaches which apply analysis on
specific gene fractions, we start approaching the problem from a system
perspective. I will work in BIG till my graduation in July, 2010.


Discovering the relation or myth between diseases and genomics will take a
pretty long time, as Prof. Lei once told me from a biologist's view: 'maybe
more than two or three centuries'. However, it is worthy of our incessant
exploration since it could help uncover the deepest myth of human - ourselves.
And what really motivates me is my interest and the greate joy involved in
analyzing the numerous data provided by Genomics, the success of which could
help in curing patients who are suffering from various diseases, [as well as the
great joy it brings when I could witness this process continuing just around
me.] (-Jeff: I don't understand this sentence.)
















